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An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing

Received: 19 August 2018    Accepted: 19 October 2018    Published: 19 November 2018
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Abstract

Lake Naivasha is an important water resource for Kenya being a fresh-water lake in a region dominated by salty-water lakes. The lake supports several human activities around it. Its water level, though fluctuates, was gradually declining before 2010. The water level rose from March 2010 and has since remained relatively high. As a result, areas around the lake that were previously land surface are currently submerged in water. This is threatening the survival of human activities around the lake. Consequently, the study sought to establish the causes of the lake’s water level fluctuations in the period 2000-2016, focusing on the role of rainfall, temperature, human activities around the lake, and water hyacinth. Surface area of the lake covered by water and surface area of the lake covered by water hyacinth were extracted from Landsat images. The SEBAL model was used to estimate evaporation potential over the lake and differences in evaporation over areas covered by water hyacinth and open water surfaces were analysed. Water hyacinth cover was found to have significant, positive correlation with monthly average water levels (p < .05). Open water surfaces lost significantly higher water volume through evaporation than areas covered by water hyacinth (p < .05). This suggests that water hyacinth contributes to the high water levels. Rainfall received over Nyandarua slopes, which is the catchment region for in-flow rivers was also an almost statistically significant contributor to lake’s water level changes, while temperature was not. On the other hand, growing human activities around the lake seemed to contribute to water level decline through increasing abstraction from the lake. The study recommends more research on, and implementation of better and more ecologically efficient measures for controlling water hyacinth growth in Lake Naivasha.

Published in American Journal of Remote Sensing (Volume 6, Issue 2)
DOI 10.11648/j.ajrs.20180602.13
Page(s) 74-88
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Lake Naivasha, Remote Sensing, Water Level, Water Hyacinth, Evaporation, Evapotranspiration

References
[1] Reta, Gebrehiwwet Legese. “Groundwater and lake water balance of Lake Naivasha using 3-D transient groundwater model.” Master Thesis, University of Twente, 2011.
[2] Ruhakana Alabert. Estimation of the change of Lake Naivasha using earth observation, GIS, and hydrological model, 2015. Accessed 22 February 2017. https://www.geotechrwanda2015.com/wp-content/uploads/2015/12/176_Albert-Ruhakana.pdf.
[3] Kyambia, Marshal M. and Mutua, Benedict M., “Detection of trends in extreme streamflow due to climate variability in the Lake Naivasha basin, Kenya,” International Journal of River Basin Management 13, no. 1 (2014): 97-103.
[4] Lal, Perakum Muthuwatta. “Long-term rainfall runoff: Lake level modelling of the Lake Naivasha basin, Kenya.” Master Thesis, International Institute for Geo-Information Science and Earth Observation, 2004.
[5] Farah, Hussein Omar. “Estimation of regional evaporation under different weather conditions from satellite and meteorological data: A case study in the Naivasha basin, Kenya.” PhD Thesis, Wageningen University, 2001.
[6] Arlan, Perkasa Lukman. Regional impact of climate change and variability on water resources Lake Naivasha basin, Kenya. Queensland: ITC, 2003.
[7] Odongo Vincent O., Christian van der Tol, Pieter R. van Oel, Frank M. Meins, Robert Becht, Japheth Onyando, and Zhongbo Su. “Characterisation of hydroclimatological trends and variability in the Lake Naivasha basin, Kenya,” Hydrological Processes, 29, Issue 15 (January 2015): 3276-3293.
[8] Trottman, Damali K. “Modelling groundwater storage change in response to fluctuating levels of Lake Naivasha, Kenya.” Master Thesis, International Institute for Aerospace Survey and Earth Sciences (ITC), 1998.
[9] Bergner, Adreas G. N., Martin H. Trauth, and Bodo Bookhagen. “Paleoprecipitation estimates for the Lake Naivasha basin (Kenya) during the last 175 k. y. using a lake-balance model,” Global and Planetary Change 36 (March 2003): 117-136.
[10] Becht, Robert, Eric O. Odada, and Sarah Higgins. “Lake Naivasha: Experience and lessons learned brief,” In Lake basin management initiative: Experience and lessons learned briefs, 277-298. Kusatsu: International Lake Environment Committe Foundation (ILEC), 2005.
[11] Dergachev V. A., O. M. Raspopov, F. Damblon, H. Jungner, and G. I. Zaitseva. Natural climate variability during the Holocene. Radiocarbon 49, no. 2 (2007): 837-854.
[12] World Lake Database, n. d. Lake Naivasha, International Lake Environment Committee. Available at http://wldb.ilec.or.jp/Details/Data/10204/Lake%20Naivasha. Accessed 27 January 2017.
[13] Mironga, John M., J. M. Mathooko, and Simon M. Onywere. “The effect of water hyacinth (eichhornia crassipes) infestation on phytoplankton productivity in Lake Naivasha and the status of control,” Journal of Environmental Science and Engineering 5 (2011): 1252-1260.
[14] University of Leicester. “Saving Kenya's Lake Naivasha: Efforts to improve sustainability.” ScienceDaily. Last Modified March 2011. Accessed 21 January 2017. www.sciencedaily.com/releases/2011/05/110511075034.htm.
[15] Makhanu, K. S.“Impact of water hyacinth on Lake Victoria.” In Water and Sanitation for All: Partnerships and Innovations, 165-166. Paper presented at the Proceedings of the 23rd WEDC Conference, Durban, South Africa, 1997.
[16] Chamier, Jessica, Klaudia Schachtschneider, David C. le Maitre, Pete J. Ashton, and Brian van Wilgen. “Impacts of invasive alien plants on water quality, with particular emphasis on South Africa,” Water SA 38, no. 2 (April 2012): 345-356.
[17] Gorgens A., and B. W. van Wilgen. “Invasive alien plants and water resources: An assessment of current understanding, predictive ability and research challenges,” South African Journal of Science 100, Issue 1-2 (January/February 2004): 27-34.
[18] Awange, Joseph L., Ehsan Forootan, Jurgen Kusche, John B. K. Kiema, P. A. Omondi Bernhard Heck, Kevin Fleming, S. O. Ohanya, and Rodrigo M. Goncalves. “Understanding the decline of water storage across the Ramser-Lake Naivasha using satellite-based methods,” Advances in Water Resources 60 (July 2013): 7-23.
[19] Kumar, G. Dinesh, B. M. Purushothaman, M. S. Vinaya, M. S., and S. Suresh Babu. “Estimation of evapotranspiration using MODIS sensor data in Udupi District of Karnataka, India,” International Journal of Advanced Remote Sensing and GIS, 3, Issue 1 (2014): 532-543.
[20] Mutiga, Jeniffer K., Zhongbo Su, and Tsehaie Woldai. “Using satellite remote sensing to assess evapotranspiration: Case study of the upper Ewaso Ng’iro north basin, Kenya,” International Journal of Applied Earth Observation and Geoinformation 125 (February 2010): S100-S108.
[21] Peng, J., Y. Liu, X. Zhao, and A. Loew. “Estimation of evapotranspiration from MODIS TOA radiances in the Poyang lake basin, China,” Hydrology and Earth System Sciences 17 (2013): 1431-1444.
[22] Sun, Zhigang., Q-X Wang, Bunkei Matsushita, Takehiko Fukushima, Zhu Ouyang, and Masataka Watanabe “Development of a simple remote sensing evapotranspiration model (Sim-ReSET): Algorithm and model test,” Journal of Hydrology 376, Issue 3-4 (October 2009): 476-485.
[23] Lu, Shanlong, Ninglei Ouyang, Bingfang Wu, Yongping Wei, and Zelalem Tesemma. “Lake water volume calculation with time series remote sensing images,” International Journal of Remote Sensing, 34 no. 22 (September 2013): 7962-7973.
[24] Widyasamratri, Hasti, Kazuyoshi Souma, Tadashi Suetsugi, Hiroshi Ishidaira, Yutaka Ichikawa, Hiroshi Kobayashi, and Ichiko Inagaki. “Air temperature estimation from satellite remote sensing to detect the effect of urbanization in Jakarta, Indonesia,” Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 4, no. 6 (2013), 800-805.
[25] Qin, Zhihao, Arnon Karnieli, and Pedro Berliner, “A mono-algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel–Egypt border region,” International Journal of Remote Sensing 22 no. 18 (November 2001): 583–594.
[26] Smith, R. B. “The heat budget of the earth’s surface deduced from space.” Yale. edu, 2010. Accessed 15 June 2017. http://yceo.yale.edu/sites/default/files/files/Surface_Heat_Budget_From_Space.pdf.
[27] Sun, Zhigang, Mekonnen Gebremichael, Qinxue Wang, Junming Wang, Ted W. Sammis T. W., and Alecia Nickless. “Evaluation of clear-sky incoming radiation estimating equations typically used in remote sensing evapotranspiration algorithms,” Remote Sensing 5 (September 2013): 4735–4752.
[28] Murray, F. W. “On the computation of saturation vapour pressure,” Journal of Applied Meteorology 6 (February 1967): 203-204.
[29] Vaisala. Humidity conversion formulas: Calculation formulas for humidity. Helsinki: Vaisala Oyj, 2013.
[30] Martin, Marlo, and Paul Berdahl. “Characteristics of infrared sky radiation in the United States,” Solar Energy 33, no. 3-4 (1984): 321-336.
[31] Jackson, Ray D., William P. Kustas, and Bhaskar J. Choudhury. “A reexamination of the crop water-stress index,” Irrigation Science 9, no. 4 (October 1988): 309-317.
[32] Linacre, E., and B. Geerts. “Roughness length.” Das UWYO.edu, 1999. Accessed 16 May 2017. http://www-das.uwyo.edu/~geerts/cwx/notes/chap14/roughness.html.
[33] Brutsaert, Wilfried. Evaporation into the atmosphere. Dordrecht: Springer, 1982.
[34] Southeast Exotic Pest Control Council. “Southeast Exotic Pest Plant Council Invasive Plant Manual.” SE-EPPC. org. Accessed 16 May 2017. https://www.se-eppc.org/manual/EICR.html.
[35] Blumel, Klaus. “A simple formula for estimation of the roughness length for heat transfer over partly vegetated surfaces,” Journal of Applied Meteorology 38, no. 6 (June 1999): 814-829.
[36] Singh, Ramesh K., and Gabriel B. Senay. “Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States,” Water 8, no. 1 (2016): 1-19.
[37] Mkhwanazi, Mcebisi, Jose L. Chavez, Allan A. Andales, and Kendal DeJonge. “SEBAL-A: A remote sensing ET algorithm that accounts for advection with limited data. Part I: Development and validation.” Remote Sensing 7, no. 11 (November 2015): 15046–15067.
[38] Zahira, Souidi, Hamimed Abderrahmane, Khalladi Mederbal, and Donze Frederic. “Mapping latent heat flux in the western forest covered regions of Algeria using remote sensing data and a spatialized model.” Remote Sensing 1, no. 4 (2009): 795-817.
[39] Ahluwalia, V. K., and Sudha Raghav. Comprehensive experimental chemistry. New Delhi: New Age International, 1997.
[40] Vincent, Christopher E., T. C. Davies, and A. K. C. Beresford. “Recent changes in the level of lake Naivasha, Kenya, as an indicator of equatorial Westerlies over Eastern Africa,” Climate Change 2, Issue 2 (1979): 175-189.
[41] Kateregga, Eseza, and Thomas Sterner. “Lake Victoria fish stocks and the effects of water hyacinths on the catchability of fish. Environment for Development,” The Journal of Environment & Development 18, Issue 1 (2009): 62-78.
[42] Mekonnen, M. M., A. Y. Hoekstra, and R. Becht. “Mitigating the water footprint of export cut flowers from the Lake Naivasha Basin, Kenya,” Water Resource Management 26 (October 2012): 3725–3742.
[43] Kull, Daniel. “Connections between recent water level drops in Lake Victoria, dam operations and drought,” International Rivers Org., 2006. Accessed 19 January 2017. http://www.internationalrivers.org/files/attached-files/full_report_pdf.pdf.
[44] Rupasingha, R. A. P. “Use of GIS and RS for assessing lake sedimentation processes: Case study for Naivasha lake, Kenya.” Master Thesis, International Institute for Geo-Information Science and Earth Observation Enschede, 2002.
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  • APA Style

    Peter Odoyo Agutu, Moses Karoki Gachari, Charles Ndegwa Mundia. (2018). An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing. American Journal of Remote Sensing, 6(2), 74-88. https://doi.org/10.11648/j.ajrs.20180602.13

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    ACS Style

    Peter Odoyo Agutu; Moses Karoki Gachari; Charles Ndegwa Mundia. An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing. Am. J. Remote Sens. 2018, 6(2), 74-88. doi: 10.11648/j.ajrs.20180602.13

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    AMA Style

    Peter Odoyo Agutu, Moses Karoki Gachari, Charles Ndegwa Mundia. An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing. Am J Remote Sens. 2018;6(2):74-88. doi: 10.11648/j.ajrs.20180602.13

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  • @article{10.11648/j.ajrs.20180602.13,
      author = {Peter Odoyo Agutu and Moses Karoki Gachari and Charles Ndegwa Mundia},
      title = {An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing},
      journal = {American Journal of Remote Sensing},
      volume = {6},
      number = {2},
      pages = {74-88},
      doi = {10.11648/j.ajrs.20180602.13},
      url = {https://doi.org/10.11648/j.ajrs.20180602.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20180602.13},
      abstract = {Lake Naivasha is an important water resource for Kenya being a fresh-water lake in a region dominated by salty-water lakes. The lake supports several human activities around it. Its water level, though fluctuates, was gradually declining before 2010. The water level rose from March 2010 and has since remained relatively high. As a result, areas around the lake that were previously land surface are currently submerged in water. This is threatening the survival of human activities around the lake. Consequently, the study sought to establish the causes of the lake’s water level fluctuations in the period 2000-2016, focusing on the role of rainfall, temperature, human activities around the lake, and water hyacinth. Surface area of the lake covered by water and surface area of the lake covered by water hyacinth were extracted from Landsat images. The SEBAL model was used to estimate evaporation potential over the lake and differences in evaporation over areas covered by water hyacinth and open water surfaces were analysed. Water hyacinth cover was found to have significant, positive correlation with monthly average water levels (p < .05). Open water surfaces lost significantly higher water volume through evaporation than areas covered by water hyacinth (p < .05). This suggests that water hyacinth contributes to the high water levels. Rainfall received over Nyandarua slopes, which is the catchment region for in-flow rivers was also an almost statistically significant contributor to lake’s water level changes, while temperature was not. On the other hand, growing human activities around the lake seemed to contribute to water level decline through increasing abstraction from the lake. The study recommends more research on, and implementation of better and more ecologically efficient measures for controlling water hyacinth growth in Lake Naivasha.},
     year = {2018}
    }
    

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  • TY  - JOUR
    T1  - An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing
    AU  - Peter Odoyo Agutu
    AU  - Moses Karoki Gachari
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    T2  - American Journal of Remote Sensing
    JF  - American Journal of Remote Sensing
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    UR  - https://doi.org/10.11648/j.ajrs.20180602.13
    AB  - Lake Naivasha is an important water resource for Kenya being a fresh-water lake in a region dominated by salty-water lakes. The lake supports several human activities around it. Its water level, though fluctuates, was gradually declining before 2010. The water level rose from March 2010 and has since remained relatively high. As a result, areas around the lake that were previously land surface are currently submerged in water. This is threatening the survival of human activities around the lake. Consequently, the study sought to establish the causes of the lake’s water level fluctuations in the period 2000-2016, focusing on the role of rainfall, temperature, human activities around the lake, and water hyacinth. Surface area of the lake covered by water and surface area of the lake covered by water hyacinth were extracted from Landsat images. The SEBAL model was used to estimate evaporation potential over the lake and differences in evaporation over areas covered by water hyacinth and open water surfaces were analysed. Water hyacinth cover was found to have significant, positive correlation with monthly average water levels (p < .05). Open water surfaces lost significantly higher water volume through evaporation than areas covered by water hyacinth (p < .05). This suggests that water hyacinth contributes to the high water levels. Rainfall received over Nyandarua slopes, which is the catchment region for in-flow rivers was also an almost statistically significant contributor to lake’s water level changes, while temperature was not. On the other hand, growing human activities around the lake seemed to contribute to water level decline through increasing abstraction from the lake. The study recommends more research on, and implementation of better and more ecologically efficient measures for controlling water hyacinth growth in Lake Naivasha.
    VL  - 6
    IS  - 2
    ER  - 

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Author Information
  • Institute of Geomatics, GIS and Remote Sensing, Dedan Kimathi University of Technology, Nyeri, Kenya

  • Institute of Geomatics, GIS and Remote Sensing, Dedan Kimathi University of Technology, Nyeri, Kenya

  • Institute of Geomatics, GIS and Remote Sensing, Dedan Kimathi University of Technology, Nyeri, Kenya

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